Automated Computational Design of Composite Li-ion Battery Electrodes Microstructures

PI：Soghrati，Soheil Proposal number：1608058拟议研究的目标是开发一种集成的计算方法来模拟和预测锂离子电池的电极性能。理解和开发锂离子电池的模型具有非常重要的价值，因为这些模型非常常见地用于储能。拟议的研究可以通过取代目前应用的试错法来设计电极，从而提高混合动力汽车和电动汽车的应用性能。这项研究将通过集成计算材料工程(ICME)方法量化用于锂离子电池(LIB)的复合电极的最佳微结构特征。虽然LIBS是二次储能的主要技术，但仍需取得重大进展，以提高其功率和能量密度，以便在交通运输领域应用。通过优化电极设计来最大化导电性和比表面积，可以显著提高LiBS的性能。然而，由于无法对这种复合材料复杂的异质结构进行逼真的建模，目前的设计过程主要是试错实践，往往导致次优设计和大量的开发时间和成本。这一建议旨在通过开发一种新的设计优化框架来克服这一障碍，该框架包括：(I)提取电极微结构的分层多尺度成像数据；(Ii)开发基于成像数据自动创建电极异质结构的逼真虚拟模型的能力；(Iii)使用先进的有限元方法模拟电极的多物理响应；(Iv)通过硬币电池原型的实验测试来验证模型；(V)通过多目标遗传算法确定产生最高功率和能量密度的最佳微结构。分层界面丰富有限元方法(HIFEM)将作为模拟充放电循环过程中电极多物理行为的主要计算引擎。HIFEM的精度和收敛速度与使用与问题形态完全无关的简单结构网格的标准有限元方法相同。HIFEM将与依赖于非均匀有理基样条(NURBS)的虚拟原型算法相集成，以基于包括X射线显微层析成像、聚焦离子束层析成像和电子显微镜在内的分层成像数据来创建复合电极的逼真3D微结构模型。为了准确地预测与不同设计的电极相关的功率和能量密度，将采用高保真计算模型来模拟LiB的电化学-机械响应。此外，将为这条自动化计算管道部署一个完全并行的计算模块，以创建电极的虚拟微结构模型并模拟其多物理行为。如果成功，拟议的项目将导致为复合电极的虚拟设计开发一个计算框架。通过这项研究产生的基本知识将使在其产品中大量使用LIBS的几个行业受益，如汽车、航空航天和便携式电子产品。此外，在本项目期间将开发的建模能力可用于处理具有类似微结构复杂性的更广泛的ICME问题。为了将研究、推广和教育整合到这个项目中，将开展以下工作：(I)强大的WWW和社交媒体影响力，以促进与公众和科学界的接触；(Ii)参与由俄亥俄州立大学(OSU)组织的K-12推广计划；(Iii)培训和指导研究生和本科生，并将研究成果纳入课程；(Iv)通过将工程研究转化为K-8计划，向中学生进行推广，该计划还将聘请俄亥俄州立大学的本科生研究助理担任职业大使。

PI: Soghrati, SoheilProposal Number: 1608058The goal of the proposed research is to develop an integrated computational approach to model and predict the performance of electrodes in Li-ion batteries. The value of understanding and developing models for Li-ion batteries is very significant, since these are very commonly used for energy storage. The proposed research could lead to improved performance for applications in hybrid and electric vehicles, by replacing the currently applied trial and error approach to electrode design. This research will quantify the optimal microstructural features of composite electrodes used in lithium-ion batteries (LIBs) via an integrated computational materials engineering (ICME) approach. While LIBs are the primary technology for secondary energy storage, significant advancements are still needed to improve their power and energy densities for application in the transportation sector. Remarkable improvement in the LIBs performance can be achieved by optimizing the electrode design to maximize the conductivity and surface areas. However, due to inability to realistically model the intricate heterostructure of this composite material, design processes are currently dominated by trial-and-error practices, often leading to sub-optimal designs and significant development time and cost. This proposal aims at overcoming this barrier by developing a new design optimization framework consisting of: (i) extracting hierarchical multiscale imaging data of the electrode microstructure; (ii) developing the ability to automatically create realistic virtual models of the electrode heterostructure based on imaging data; (iii) simulating the multiphysics response of the electrode using an advanced finite element method; (iv) validating the models via experimental testing of coin-cell prototypes; (v) identifying the optimal microstructures that yield highest power and energy densities via a multi-objective genetic algorithm. A hierarchical interface-enriched finite element method (HIFEM) will serve as the main computational engine for simulating the multiphysics behavior of the electrode during charge/discharge cycles. The HIFEM yields the same precision and convergence rate as those of the standard FEM using simple structured meshes that are completely independent of the problem morphology. The HIFEM will be integrated with a virtual prototyping algorithm relying on Non-Uniform Rational Basis Splines (NURBS) to create realistic 3D microstructural models of the composite electrode based on hierarchical imaging data involving x-ray microtomography, focused ion beam tomography, and electron microscopy. To accurately predict the power and energy densities associated with various designs of the electrode, a high fidelity computational model will be implemented to simulate the electro-chemo-mechanical response of the LIB. Furthermore, a fully parallel computing module will be deployed for this automated computational pipeline to both create virtual microstructural models of the electrode and simulate its multiphysics behavior. If successful, the proposed project will lead to the development of a computational framework for the virtual design of composite electrodes. The fundamental knowledge generated through this research will benefit several industries heavily using LIBs in their products, such as the automotive, aerospace, and portable electronics. Moreover, the modeling capabilities that will be developed during the term of this project can be employed for the treatment of a broader range of ICME problems with similar microstructural complexities. To integrate the research, outreach, and education in this project, these tasks will be pursued: (i) strong www and social media presence to facilitate outreach to the public and scientific communities; (ii) participating in K-12 outreach programs organized by Ohio State University (OSU); (iii) training and mentoring of graduate and undergraduate students and integrating research outcomes into the curriculum; (iv) outreach to middle school students via Translating Engineering Research to K-8 program, which will also engage OSU's undergraduate research assistants as career ambassadors.